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<table width="100%" summary="page for azcabgptca"><tr><td>azcabgptca</td><td style="text-align: right;">R Documentation</td></tr></table>

<h2>azcabgptca</h2>

<h3>Description</h3>

<p>Random subset of the 1991 Arizona Medicare data for patients hospitalized 
subsequent to undergoing  a CABG (DRGs 106, 107) or PTCA (DRG 112) 
cardiovascular procedure. 
</p>


<h3>Usage</h3>

<pre>data(azcabgptca)</pre>


<h3>Format</h3>

<p>A data frame with 1959 observations on the following 6 variables.
</p>

<dl>
<dt><code>died</code></dt><dd><p>systolic blood pressure of subject</p>
</dd>
<dt><code>procedure</code></dt><dd><p>1=CABG; 0=PTCA</p>
</dd>
<dt><code>gender</code></dt><dd><p>1=male; 0=female</p>
</dd>
<dt><code>age</code></dt><dd><p>age of subject</p>
</dd>
<dt><code>los</code></dt><dd><p>hospital length of stay</p>
</dd>
<dt><code>type</code></dt><dd><p>1=emerg/urgent; 0=elective</p>
</dd>
</dl>



<h3>Details</h3>

<p>azcabgptca is saved as a data frame.
</p>


<h3>Source</h3>

<p>Hilbe, Negative Binomial Regression, 2nd ed, Cambridge Univ Press
</p>


<h3>References</h3>

<p>Hilbe, Joseph M (2014), Modeling Count Data, Cambridge University Press
</p>


<h3>Examples</h3>

<pre>

data(azcabgptca); attach(azcabgptca)
table(los); table(procedure, type); table(los, procedure)
summary(los)
summary(c91a &lt;- glm(los ~ procedure+ type, family=poisson, data=azcabgptca))
modelfit(c91a)
summary(c91b &lt;- glm(los ~ procedure+ type, family=quasipoisson, data=azcabgptca))
modelfit(c91b)
library(sandwich)
sqrt(diag(vcovHC(c91a, type="HC0")))
</pre>


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